368 computer-architecture-"https:"-"https:" positions at Oak Ridge National Laboratory
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scalable applications for future architectures through the use of proxy or mini-applications. Applying large-scale computational methodologies to meet scientific objectives. Conduct research and report
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, architecture/design implementation, testing, configuration management, and issues management. Collaborate with multidisciplinary engineering teams to translate system requirements into actionable software
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technology remain secure. The team is collaborative and strives to ensure security practices and procedures are understood, implemented, and enforced. Major Duties/Responsibilities: System Design and Architecture
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architecture, and ORNL’s enterprise and high-performance computing (HPC) environments. The role is typically less about building individual models and more about designing, integrating, and governing end-to-end
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such as quantum and analog computational models. You will explore how compilers, runtimes, and AI-driven agents can co-optimize complex architectures, reasoning across conventional processors (CPUs/GPUs
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candidate will bring a strong foundation in systems architecture, a working knowledge of cluster computing and scaling, and a passion for advancing the security of AI systems under real-world and simulated
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candidate will bring a strong foundation in systems architecture, a working knowledge of cluster computing and scaling, and a passion for advancing the security of AI systems under real-world and simulated
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interface across multiple layers—from user-facing applications, system infrastructure and networking. You will apply systems engineering principles throughout the lifecycle (requirements, architecture
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Requisition Id 16485 Overview: The Data and AI Systems Research Section within the Computer Science and Mathematics Division at Oak Ridge National Laboratory (ORNL) is seeking a postdoctoral
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scientific capability, focusing on the co-evolution of algorithms, models, data, and computing architectures. Establish R&D priorities across: AI foundation models trained on scientific and simulation data